Scientific data in China to unveil more shining treasures under new regulations

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The State Council of China recently issued regulations on scientific data management, effective as of 17 Mar 2018. The new regulations clearly stressed an obligation to open scientific data to a boarder society with supports from public funding.

The regulations defined the concept of scientific data, and clarified some issues concerning data sharing, including different stakeholders’ responsibility in scientific data stewardship, rules for data collection and long-term preservation, rules for data sharing and application, together with privacy and public safety issues. Among the contents include rewards and punishments for data reuse, which is to guarantee a smooth implementation of the new regulations. Highlights also include to establish data quality control systems and data filing mechanisms, as well as to promote classification-based lifecycle data curation & sharing.

Prior to this, many national-level data programs had taken the lead in facilitating data production and reuse, such as the “National Science and Technology Infrastructure”(2001-) supported by the MOST, the “Chinese Academy of Sciences Database" program (1986-), the newly-initiated A-class strategic high-tech research program ”Big Earth Data Project”, as well as data projects of the National Natural Science Foundation of China (NSFC) and the China Association for Science and Technology (CAST), among others.

So far, it is the first state-level official document featuring comprehensive scientific data stewardship covering all research disciplines. The new regulations constitute a landmark in the history of scientific data sharing in China. Undoubtedly, the promulgation of the regulations shall start a new era for China’s research community and boom scientific research at an even accelerated speed. As one of the most productive place in the world, China shall play an even more vital part, both locally and globally, in promoting the findability, accessibility, interoperability and reusability of research data.